Growthology

Today's Readings Relevant to Entrepreneurship

The intersection between tight labor markets, housing costs, and the opportunity cost of entrepreneurship: Free Exchange. The work by Fairlie and Chatterji that Ryan cites here is terrifically important and has not gotten nearly enough attention.

Why is carried interest taxed as it is? Observational Epidemiology. 

What the studies say about private equity. Dealbook (via Marginal Revolution). Tyler sums it up: "'Some positives, lots of uncertainty' would be a good description of the available evidence."

Brad Feld on the intra-metropolitan geography of entrepreneurship. We probably need some new mapping tools. Feld Thoughts.

As an aside, I completely agree with Brad that "entrepreneurial density" is a good measure of a region's culture of entrepreneurship, but I don't know if we can yet measure it precisely. For one thing, we need to agree on a common definition of entrepreneurship. Then we need to figure out how to count it--government data are not entirely helpful here. Then we need to figure out what it means. One of our research assistants has been looking over Business Dynamics Statistics data on employment in young firms as a share of total employment in each state over the past three decades. We will post some charts and findings soon, but as the data relate, so far, to existing literature, I am reminded of The Princess Bride:

Vizzini: "He didn't fall? INCONCEIVABLE!"

Inigo Montoya: "You keep using that word. I do not think it means what you think it means."

(h/t to PK for the reminder of this pricelessly fungible line the other day)

President Obama Promotes Entrepreneurship

In case you missed it, here is President Obama in the State of the Union speech last night, underscoring the important role of entrepreneurs:

It means we should support everyone who’s willing to work, and every risk-taker and entrepreneur who aspires to become the next Steve Jobs. After all, innovation is what America has always been about. Most new jobs are created in start-ups and small businesses. So let’s pass an agenda that helps them succeed. Tear down regulations that prevent aspiring entrepreneurs from getting the financing to grow.

This may have been a reference to the Startup Act, versions of which have been introduced in both the House and Senate. Even so, any mention by the president of the vital role that new companies play in economic growth is noteworthy, especially because, as many claim, public celebration of entrepreneurs is an important cultural attribute.

The Ongoing Debate Over Small Business and Job Creation

My Kauffman colleague E.J. Reedy wrote an insightful post at Data Maven on Carl Bialik's somewhat disappointing Numbers Guy column over the weekend about job creation by small business. These come on the heels of Charles Kenny's well-done essay in Bloomberg Businessweek about the various nuances involved in counting job creation by business size and the distortions that often arise.

We continue to do research and analysis on these issues--one of the exciting things about entrepreneurship research is that every time we learn something new, we realize how much there remains to understand. What's clear, and what E.J. underscores, is that we should not be satisfied with aggregate data. They help us penetrate to one level of understanding, but aggregate data also introduce another slew of distortions and obscurities. E.J. pointed out that firm age and local/non-local are two important distinctions. I would also add the sectoral lens--the more time I spend with the numbers the more I'm convinced that sectoral breakdowns explain a significant share of what we see in terms of new and young businesses, small businesses, job creation, and churn. There is still quite a bit of work to do, however, and I'm happy to disprove my own hypothesis.

The three essential messages of Steve Jobs (so far)

The retirement of Steve Jobs as CEO of Apple is perhaps a bigger earthquake in the world of technology than we realize. The "eruption" of adulation, as Will Wilkinson (blogging at Economist.com) calls it is entirely deserved but can't help but mask the depth of meaning underneath the simple story of one man stepping down.  The essential messages of the Steve Jobs' life story are three.  First, he more than anyone is the icon of the boomer generation of American entrepreneurs, even more than Bill Gates. Second, Jobs (and Steve Wozniak) completely upended the prevailing model of economic progress of the 20th century, which was understood as technological discovery stemming from the academic or corporate laboratory.  Third, by returning to Apple in 1996, twenty years after founding the company, then leading it from near bankruptcy to dominance in a decade - with a current market capitalization of $346 billion (exceeding other tech giants such as Microsoft at $207b and Google at $169b) - Steve Jobs has powerfully affirmed the idea of the 'great man' in history.  

Born in 1955, the man essentially emerged from nowhere: he is not from a well-connected family (indeed, was adopted soon after birth) and did not attend or graduate from a top college. He tinkered, showed enough interest in computers in high school (in the very early 1970s) to hang around Hewlett-Packard, and collected coke bottles in order to have spare change for food.  This is reminiscent of the humble origin of the superhero (part of the American mythos) save this: Clark Kent was a farmboy not suburban hacker. And Peter Parker got his superpowers from a science lab accident, not from tinkering in the garage. 

Years ago, when the triumphant gaze of Bill Gates loomed over the stage where Jobs announced a major Microsoft investment in the new Apple Corporation, many realized that Jobs was actually the larger man.  This discounts nothing from Gates and his legacy, but the key distinction between them is glamor, or elegance, or charisma. Perhaps the ultimate design achievement of Steve Jobs was Steve Jobs.  With over hundreds of patents, the CEO is also the real deal in terms of innovation. And by God, does he have his flaws. So?  He's authentic, not perfect. And his authentic genius is understanding better than anyone how to make technology so easy that it becomes profound, obvious, and yes magical.

I speak often about the big sweep of history, particularly how relentless economic growth changes the human condition.  And I almost always call out Steve Jobs and Steve Wozniak because their story represents a stunning refutation of the consensus paradigm of progress that held sway over serious thinkers for almost all of the 20th century, certainly the middle five decades.  Even Joseph Schumpeter, the celebrated prophet of innovation and champion of the heroic entrepreneur believed that the new era would inevitably see the dominance of corporatism and its efficient R&D labs.  Not until the rise of Silicon Valley and its startup culture affirmed the pioneering success of Apple did the consensus shift, quietly, as if nothing had changed.

The recognition of startups, not governments, as the central actors in economic history should not be neglected after you turn this page.  As the great Apple chronicler Robert X. Cringely noted, "Apple has more cash on hand than does the U.S. government." And it has that cash for a reason, not to deny jobs to hungry Americans, but to invest in ever leaner supply chains making magical new products affordable to everyone. That, folks, is a big fracking deal.

“Innovation has nothing to do with how many R&D dollars you have. When Apple came up with the Mac, IBM was spending at least 100 times more on R&D. It’s not about money. It’s about the people you have, how you’re led, and how much you get it.” - Steve Jobs, Fortune, Nov. 9, 1998

The American economy has been the strongest in the world for nearly a hundred years.  Its growth has been built on the innovations of great entrepreneurs like Henry Ford and the Wright brothers.  Thanks to the boomer entrepreneurs, that legacy has been reaffirmed.  Best of all, we now know that hard work and competitiveness are what matter, not class. Jobs represents the triumph of intelligence, of merit, over fate. You could not script the American dream with a more compelling central character.

CORRECTION: THe original post stated Steve Jobs was born in 1995. The correct date is 1955.  

Entrepreneurs Are Natural Hayekians

In the airport on the way back from this conference, I picked up a copy of the current issue of Inc. magazine for the cover story on "How Great Entrepreneurs Think." The article relates the results of a study by UVA Darden School professor Saras Sarsvathy of 45 top entrepreneurs. All were presented with a case study of a hypothetical start-up and then quizzed about how they would run it. Interestingly, she later conducted the same exercise with managers at large corporations. The differences in thinking and decsion-making style are instructive:

Sarasvathy likes to compare expert entrepreneurs to Iron Chefs: at their best when presented with an assortment of motley ingredients and challenged to whip up whatever dish expediency and imagination suggest. Corporate leaders, by contrast, decide they are going to make Swedish meatballs. They then proceed to shop, measure, mix, and cook Swedish meatballs in the most efficient, cost-effective manner possible.

So, for example, when one entrepreneur was asked about what market research would be needed, he replied:

"I don't believe in market research. Somebody once told me that the only thing you need is a customer. Instead of asking all the questions, I'd try and make some sales. I'd learn a lot, you know: which people, what were the obstacles, what were the questions, which prices work better."

Here's another quote along similar lines:

"I always live by the motto of 'Ready, fire, aim.' I think if you spend too much time doing 'Ready, aim, aim, aim,' you're never going to see all the good things that would happen if you actually started doing it. I think business plans are interesting, but they have no real meaning, because you can't put in all the positive things that will occur...."

Generalizing from these kinds of attitudes, Sarasvathy concludes that entrepreneurs

do not believe in predictions of any kind. "If you give them data that has to do with the future, they just dismiss it," she says. "They don't believe the future is predictable ... or they don't want to be in a space that is very predictable."

Which means -- segueing now from practice to theory -- that entrepreneurs grasp intuitively the central insight of the great economist F. A. Hayek: that capitalism is a process of discovery. Hayek saw that socialist central planning, then at the height of intellectual fashion, was doomed to founder on the unpredictability of the future. Capitalism, at the time derided for its chaotic duplicativeness, worked precisely because of its messiness: its decentralized process of trial-and-error experimentation is the only viable response to the ineradicable uncertainties of economic life. 

Entrpreneurs are Hayekians at the micro level. They don't want to sit back and plan, they want to dive in and discover and learn. They want to experiment: to see what works and what doesn't, to build on the successes and leave the failures behind. Which is exactly what how the larger market order works at the macro level.

None of this is to say that planning is unnecessary. On the contrary, it's vital -- after you've discovered a good idea. To take that idea to scale and execute it efficiently -- in other words, to pump out those Swedish meatballs -- you need planning and lots of it. Which is why successful start-ups turn into big corporations run by professional managers.

Here's Sarasvathy's full case study. 

Time to Think About the Egyptian Economy

Now that Egypt has experienced a democratic revolution military coup, underlying problems in its economy must be addressed. Bob Litan and I argue, not surprisingly, that entrepreneurship needs to be a key piece of the Egyptian economic future:

Karl Marx famously insisted that a society's workers, not the bourgeoisie, must own the "means of production." But for broadly shared growth to take hold—for entrepreneurial capitalism to develop—the people must own the economy in a different manner. The must have the opportunity and the motivation to start and grow new companies. 

More here. (Carl Schramm gets full credit for this neat twist on Marxist thought.)

Many other countries need to chart the same course. Pakistan: pay careful attention.

Entrepreneurship in Egypt

Elmira Bayrasli:

Egypt is more populous and poorer today than it was 20 years ago.  But it is also more literate and connected to the world.  That is good and bad.  Young Egyptians are developing skills and becoming more aware of the opportunities around the world – (and the lack of them in their own country).  You extrapolate.

Increased freedoms would go far to ensure that these youth can access those opportunities.  Expanding entrepreneurship would guarantee it.  As much as Egyptians need and deserve freedom, they need and deserve the tools that will allow them to build vibrant and sustainable businesses.

More here, including some great numbers.

 

More on Pakistan's Economy

Good post today by Nancy Birdsall, Wren Elhai, and Molly Kinder of the Center for Global Development on the challenges of Pakistani political economy:

U.S. policymakers should note well this series of events and remember a simple lesson. Billions of dollars of U.S. assistance-and a sustained diplomatic focus on the reform agenda-have not given the United States the ability to dictate the outcomes of Pakistan's political process. This is inconvenient for the United States, but not surprising. For the United States and for other major donors in Pakistan, money has never brought leverage.

They present some very good options for more effective ways the United States and the international community can use aid to force change. Our question from the other day still stands: what can we do now to promote and support entrepreneurship in Pakistan? Aid only takes you so far (or, in some cases, takes you backwards).

Some Puzzles about Entrepreneurship and Entrepreneurial Capitalism

The standard narrative about the American economy in the late twentieth century typically runs as follows: after four decades of quasi-statist capitalism (the 1940s through the 1970s) that brought the United States to the brink of economic ruin, the economy experienced an entrepreneurial explosion around 1980. The economy moved from the dull bureaucratic capitalism of the "Organization Man" to the exciting entrepreneurial capitalism of high-technology and, accordingly, more robust growth and productivity. Without questioning the importance of entrepreneurship to economic growth, I'm beginning to wonder about this.

For starters, let's take recent technological history. The information technology revolution that is associated with the 1980s and 1990s was born in the 1950s and 1960s, emerging out of government-funded research performed at universities and large company laboratories. We could probably mark the start of the IT revolution at the founding of Fairchild Semiconductor 1957 or, perhaps, the founding of Intel in 1968; Microsoft and Apple followed in the mid-1970s. Other companies typically associated with this entrepreneurial rebirth include FedEx and Southwest Airlines, which were also started in the late 1960s and early 1970s. Even within the confines of the conventional narrative outlined above, we can trace the roots of entrepreneurial capitalism to the final stages of bureaucratic capitalism, a pattern that aligns with other models of technological revolutions and transitions. In his wonderful book, The Age of Abundance, Brink Lindsey (who is now a Senior Fellow at the Kauffman Foundation), connects the counter-cultural ethos of the 1960s with the subsequent entrepreneurial revolution in business.

The typical narrative of entrepreneurial capitalism is also usually supported by reference to either changing rates of overall entrepreneurship or the high number of initial public offerings (IPOs) in the 1980s and 1990s, as well as the explosion of alternative forms of financing, from junk bonds to venture capital. And, indeed, according to at least one strand of Census Bureau data, the absolute number of new incorporations did increase dramatically from the 1960s to the 1970s and again to the 1980s and 1990s. New company listings, moreover, rose from an average of 156 per year from 1973 to 1979, to 549 per year from 1980 to 2001. From 1980 to 2001, in fact, newly listed firms comprised 10 percent of all listed firms in any given year. Venture capital, too, increased by several factors from the end of the 1970s and despite reverting from its astronomical heights in the late 1990s, VC remains at historically elevated levels.

Over the last several months, however, I happened to come across several pieces of evidence--some new, some older--that would appear to contradict the typical narrative. (I am not claiming any particular insight here, nor do I intend to mean that the U.S. economy was somehow "better" in the 1960 and 1970s than today. I heartily endorse Brink's arguments in "Nostalgianomics" on this point.)

Let's start with the most basic empirical information: the number and rate of new business formation. When the Census data cited above are expressed in per capita terms, the apparent doubling of firm formation disappears: the population doubled, bringing new business creation along with it without a corresponding increase in the rate. Indeed, we have published two papers on the puzzle of relatively steady levels of entrepreneurship in the United States, both across the past thirty years (the purported period of extreme entrepreneurship) and, potentially, across the entire twentieth century. In fact, firm formation fell from the 1980s to the 1990s and then flattened, neither falling nor rising. Per capita rates of new business formation today are actually quite similar--and certainly no higher--to those in the 1940s and 1950s, the ostensible high tide of bureaucratic capitalism.

What about IPOs? Using historical data from Gompers and Lerner and more recent data from Fama and French, here are the average annual IPOs for various time periods back to 1935 (the groupings are dependent on the authors' work, not my own manipulations): 

1935-1949:    11

1950-1959:    45

1960-1972:    233

1973-1979:    37

1980-1989:    328

1990-2001:    413

The averages obviously mask variability, but it is generally true that after 1980 the United States saw sustained levels of historically high numbers of IPOs. But it is certainly not true that the era of bureaucratic capitalism was without entrepreneurial excitement. From 1959 to 1962, the average number of IPOs per year was 224. From 1968 to 1972 it was 388, a number much closer to the supposedly go-go 1990s than even the 1980s.

At the same time, the IPO explosion after 1980 brought its own issues. Fama and French found that the "decline in the cost of equity capital for new lists" meant that weaker firms could now go public. In particular, in the 1980s and 1990s the distribution of revenue growth across newly-listed firms skews to the right, meaning higher growth. Meanwhile, the distribution of profitability skewed left, meaning lower rates of profitability. Survival rates of newly listed firms also fell over this time period. As they stated: "Basically, the evidence says that weaker firms and firms whose expected payoffs are further in the future become viable candidates for public equity financing." This echoes other research finding, since the late 1970s, a dramatic rise in growth rate volatility among publicly-traded companies but a fall in the volatility of privately-held firms--nearly to the point of convergence, in fact. It is true as well that volatility among our largest companies, the Fortune 500, has risen and not quite one-fifth of today's Fortune 500 companies have been founded since 1980. But this is more an indication of turnover among existing companies, including mergers and acquisitions, rather than new firm entry. And even if more companies fall off the list, it doesn't mean they fail; it just as likely reflects the relative rise of other companies.

(Some of this also calls into question the role of high-growth firms. As the above comments indicate, rapid revenue growth does not necessarily mean profitability. This corroborates other work that examines the Inc. lists of fast-growing companies. I am a huge fan of the Inc. data and I think much more can be done with it, but we shouldn't imagine that high growth in revenues tells us anything about economic impact or long-term success. Presumably it should, but it apparently does not. I have written elsewhere that high-growth firms are neither as interesting nor important as they are typically thought to be. If the underlying dynamics of firm formation and competition are reasonably healthy, we should expect to see high-growth firms as epiphenomena of those, not necessarily drivers in themselves.)

In any case, what does any of this mean? Let's review. During the period of entrepreneurial capitalism, we have seen no increase (yet no significant decrease either) in levels of firm formation, but a larger number of IPOs and greater volatility among publicly-traded firms, indicated particularly by dispersed growth rates and profitability. This dimension in the public markets is, in part, an effect of greater availability of financing. Is what we call entrepreneurial capitalism really just a reflection of public-market volatility, itself a reflection of the rising role of finance in the American economy over the past thirty years? 

I should point out, again, that none of this is meant to imply that the last thirty years were somehow worse than the middle part of the twentieth century. Nor is it meant to exclude the dramatic changes in technology over the past three decades. Indeed, high-tech companies likely account for much of the public-market volatility. At the broader level of aggregate firm formation, sectors such as food service, administrative services, health care, and professional services (in particular lawyers) tend to predominate, particularly among high-growth firms. My points here are not a value judgment on the types of companies that are formed. But it appears that there is still quite a bit about entrepreneurship--its trends, its composition, its impact--that we do not understand. And, should we be on the cusp of an entrepreneurship boom--whether because of technology, changing economic factors, demographic factors, whatever--it remains to be seen whether, in the context of existing structural factors, this will shift us to a different neutral state. And, again, we have not even touched the impact of new companies yet; a much more extensive treatment than I have given here will also layer on technological change. So much goes on beneath the surface of aggregate entrepreneurship levels, of IPO activity, of growth and profitability, that it is difficult to make blanket claims about capitalist typology.

I could, of course, be wrong.

"Wrongology"

Immediately drop everything you are doing and read this article. Then, shove aside the growing pile of books on your nightstand and read this book this weekend (doing so will also deflate any tension with your spouse over the appearance of your nightstand). Discussion questions:

1. How can we really "know" anything? These pieces only reinforce my belief that one of the most profound philosophical statements in all of history comes to us courtesy of Bill & Ted: "The only true knowledge consists in knowing that you know nothing. That's us, dude!" (And, yes, I know I have written about this before, but really, is there anything more fundamental than the question of how we can know whether we're right or wrong?)

2. Where is the John Ioannidis of economics or social science more broadly?

3. I often think that a helpful research strategy would be to write a "bizarro" paper for every "real" research paper that we do. But I can't decide if that would have any merit or even feasibility. As Being Wrong details in such a lovely way, the most pernicious and persistent type of confirmation bias is the failure to seek out contradictory evidence--omission rather than commission. If anyone tells you how open-minded and open to criticism they are, they're probably wrong. It would seem to be much safer and saner to walk around with the presumption that you are wrong about everything until proven otherwise, but this strategy would clearly strain the limits of human identity and, thus, plausibility. 

4. If much of our conscious identity (the stories we tell ourselves) is composed of memories, but if those memories turn out to be mostly mis-remembered, what does that mean?

Finally, out of sheer coincidence, I also happened to stumble across this terrific sentence earlier today: "Both rationalism and functionalism grossly exaggerate the capacity of actors to know what they are doing before they have done it." (See question 2 above.) (HT: Rogers Hollingsworth.)

Entrepreneurship and Meaning

Virginia Postrel offers a pithy feast, a meditation on entrepreneurship and meaning.  Highlight:

The illusions that spur entrepreneurial ventures and consumer daydreams point to the nonmaterial side of markets. Markets not only expand health and comfort, providing a sustaining material existence. They also spur ambition and imagination, the quest for achievement and the pursuit of meaning. They give us an opportunity to exercise our creativity, to enjoy the satisfactions of absorbing, productive work, and to fashion and express our identities. 

Postrel challenges me to reflect: Why do I covet the consumption of new goods?  First, I dream of a longer, healthier life for my children and nephews and nieces. That alone: the prosperity of an innovative economy, is all I need to justify the irrationality of entrepreneurial capitalism. Second, a world without invention would limit my appreciation of beauty.  How else can I explain why I enjoy snow skiing (and the invention and sale of ski lift tickets)? Third, I never let myself forget how dreary life as mere survival can be. Thank SERE for that. And thank memory and imagination. Have you not heard the elders speak of working the fields, working the mines?  Those fields, and those mines, dangerous, hard, incessant.  If we imagine and strive for a world where even the poorest humans can labor without pain, we are entrepreneurs.

Repression of Entrepreneurs, Coyoto Blog edition

Typically taxation issues get a lot more attention than these regulatory issues in discussions of government drags on the economy. But these small regulations, licenses, and approvals consume management time, the most valuable commodity in small businesses that typically are driven by the energy and leadership of just one or two people.

That's from a Forbes essay by Warren Meyer, author of Coyoteblog.com.  Best line:

[W]e needed permission from the county to demolish the building the county had condemned--that cost us a couple hundred dollars and several forms.

UPDATE: Check out the follow-up post on Warren's own blog about the July 4 weekend sting on his campground.

Startups Are Everything

My new study just released from the Kauffman Foundation, The Importance of Startups in Job Creation and Job Destruction, is available now. It's short and sweet (7 pages of text), with about as simple a talking point as can be: "New firms add an average of 3 million net jobs in their first year, while older companies combined lose 1 million net jobs annually."  The surprise for me, and I expect most economists/data geeks, is that aggregate gross job creation and destruction curves along the firm age axis are convex, not concave.

I don't have the individual charts in GIF format, but here's a raw one from my spreadsheet. Notice how gross job creation at startups dwarfs gross flows at other firms. For example, startups create 10x more jobs than 10-year old firms, gross, and infinitely more net.  How many economists even guess this is how the U.S. economy works?  I didn't until I saw the data.

 

  

Why Not a Market for Advancing Innovations out of Universities?

Yesterday I had the privilege of delivering testimony on behalf of Bob Litan in front of the Joint Economic Committee. The subject of the hearing was how the United States could maintain its position on the global frontier of innovation, with a specific focus on universities and federal funding of research and development. Most of the Members of the Committee were in general agreement with the panelists: innovation is key to economic growth, universities are important to R&D and innovation, and the United States needs to make some changes if we are to remain an innovative economy.

On one particular point, however, there was a considerable degree of contention. Congresswoman Carolyn Maloney (D-NY) inquired as to the state of technology commercialization in higher education. Can it be improved? Is everything peachy-keen? 

The Kauffman Foundation takes the position that all is not well in the land of technology commercialization. There are success stories, to be sure: Gatorade, Vitamin D, Netscape, MRIs and so on. And there are star performing universities--Stanford, WARF (the Wisconsin system), and the University of California system do a phenomenal job of moving innovations out of campus buildings and into new (and existing) companies. But universities, on the whole, appear to be under-performing relative to what they could be contributing to economic growth. The Bayh-Dole Act of 1980 allowed universities to hold the intellectual property rights to innovations and discoveries that result from federally-funded research. The result was a wave of university innovations as well as a wave of attempts to move university innovations into the marketplace. Most universities receiving federal R&D dollars established technology licensing or transfer offices (TLOs or TTOs) to manage the intellectual property and serve as the liaison for faculty members seeking to commercialize their innovation. As noted, many universities have managed to successfully commercialize new technologies.

As with anything, however, the structure that was set up in response to Bayh-Dole has now run into problems. The productivity of federally-funded research at universities has been declining for a number of years. Technology transfer offices are typically understaffed and unable to manage their university's stream of innovations--innovations, moreover, that often span a wide diversity of disciplines. At the same time, however, bureaucracy has grown up around the process of technology commercialization and dramatically slowed, if not stalled, the process in many places. Anecdotal evidence abounds of faculty members running headlong into bureaucratic drywall at their licensing office. Furthermore, as a result of the outstanding success of a handful of universities with a handful of innovations, many TTOs and TLOs have implicitly or explicitly adopted a home-run mentality, chasing the next big hit at the expense of many smaller innovations. 

Finally, many universities have latched onto the most easily measured outputs of R&D, patents and licenses. But, there is little correlation between federal research funding and the returns (in patents and licenses) on that funding. Maybe we shouldn't expect there to be such a correlation, of course, but the race by universities in the wake of Bayh-Dole to establish commercialization offices and the drift of research spending toward a more political rather than scientific distribution have raised the implicit promise that there is such a correlation. The wonderful historian Roger Geiger has documented such drift: at one time, the distribution of university innovations and federal R&D money to universities both followed a Pareto distribution, with a handful of institutions far outdistancing everyone else in terms of inputs and outputs. Over time, however, while the distribution of innovative outputs remains skewed, the distribution of research dollars has gradually gotten flatter. We expect proportional output in terms of innovations but don't receive it.

There is no magic solution to these bottlenecks, but my colleagues Lesa Mitchell and Bob Litan have come up with a fantastically simple and novel idea: open up technology transfer to market competition. That is, allow a professor from University X with a potentially breakthrough innovation to go outside his or her university's TLO and use that of University Y, if University Y happens to be more skilled at commercialization in this particular discipline. University X would not be required to relinquish IP rights, and of course the professor is not required to do anything. The idea is simply to bring more openness and competition into a process that has become muddled and distorted. Where else in society do we tolerate such artificial monopolies with public research dollars at stake? This idea, in fact, perfectly carries forward and extends one of the primary motivations behind Bayh-Dole--to smooth the commercialization process. Bayh-Dole was enacted in part to construct a platform upon which faculty and professors could more easily interact with companies (new and existing). Allowing universities to hold IP rights was meant to remove one of the legal entanglements in this process.

Who could oppose such openness? Who could oppose competition when competition has been shown repeatedly to be the best avenue toward maximizing innovation and social welfare? Not to sound trite, but follow the money. Most universities and TTOs and TLOs vehemently oppose this idea. In fact, you can scroll through the webcast of yesterday's hearing to the very last question and witness the animation with which Dr. Samuel Stanley opposes the mere mention of this idea. Basically, the opposing arguments boil down to these: (a) there is no evidence that the current licensing process is dysfunctional; (b) allowing such "free agency" would give rise to all the legal problems that predated Bayh-Dole and were put to bed by that legislation; (c) no professor and no university wants to do this; (d) technology commercialization is a delicate art that cannot be commoditized; and (e) the current system is working fine as it is--as proof, look at all the great innovations universities have given us.

Unfortunately, I did not get a chance for a counter-rebuttal, so I offer it here. First, Dr. Stanley (and others) confuses an absence of evidence with evidence of absence. The absence of overt dysfunctionality does not imply the corollary, that things are hunky-dory. In fact, the arguments I've mentioned above regarding research productivity and returns to patents and licenses would seem to indicate something is amiss, as would the growing stock of anecdotes from frustrated professors and companies. It is of course nearly impossible to prove that something like a university is not living up to its perceived potential in terms of commercializing innovations, but the inability to prove that there is room for improvement is not an argument against opening up the process. That, in fact, is the nub of the free agency proposal--just open it up. No one would be forced to operate as a free agent or to contract with a free agent, as Dr. Stanley seems to think we are suggesting. This is entirely optional, as is any competitive market. It could even be optional at the level of the department or school of any particular university, with one department perhaps choosing to work with ABC agent while another chooses XYZ agent.

Dr. Stanley also predicts that such openness would instigate a return to those dark days before Bayh-Dole when legal machinations corrupted every attempt at commercialization--contract disputes, broken agreements, etc. Oddly, however, technology commercialization at universities is still plagued by these problems--Bayh-Dole did not banish legal disputes, and I'm not sure how Dr. Stanley manages to pull off such cognitive dissonance.

By opening up the technology commercialization process, we would likely see the development of completely new organizational forms to facilitate the process. No one can predict what will happen--and that is exactly the point. Maybe free agency will flop; maybe it won't. But there is no (or shouldn't be) single model when it comes to technology commercialization: free agency would encourage experimentation as a way to lower transaction costs, which was precisely the idea behind Bayh-Dole. In fact, many professors are already finding their way around the TLOs and TTOs, doing "end-runs" around the bureaucracy and finding their own commercialization routes. Rather than see this perversion as a defense of the status quo we should encourage free agency as a way to promote the development of more such alternate pathways. In their promotional materials and commencement speeches, university administrators consistently trumpet the glories of diversity and self-actualization and intellectual experimentation--except, it seems, when it comes to their own operations.

That seems to be a running theme of opposition: technology commercialization is special and cannot be subject to the rules of the market that govern the rest of the economy. Dr. Stanley is far from alone in asserting that each particular innovation is unique and must be granted its own customized commercialization process that can only be run through a TLO. Undoubtedly, there is some truth to this. Just as clearly, however, there is plenty of room to lower transaction costs by standardizing some portions of the commercialization process. This is precisely what UNC-Chapel Hill has done with the Carolina Express License Agreement; we will keep you posted as to whether or not the world ends as a result of this dangerous experimentation with technology commercialization.

Finally, we come to the tried and true defense that everything is fine. Universities have, after all, contributed enormously to economic growth and human welfare. Why mess with success? The real message, however, is: don't mess with us! This is the completely predictable and understandable response of any institution when its monopoly is threatened and should, in fact, serve as a reason to promote more experimentation. Just because universities have contributed much in the past does not mean they are performing optimally today (research is only one of many fronts on which we could have this discussion) and does not guarantee that they will continue to do so in the future. If bureaucracy keeps building up around the discovery and innovation process, it is almost guaranteed that they will not.

Who Declared War on Entrepreneurs?

Nick Schulz over at the Enterprise Blog draws our attention to an apparent crackdown by the IRS on the flexible employment arrangements used by many independent contractors and small businesses. It's not clear what impact this will have but, anecdotally at least, there have been reports that many new and young businesses in this recession have been turning more and more to freelancers and contractors. And we've seen the average size of new companies shrink over the past few years by about two employees--as noted in the story above, this likely indicates increasing use of such flexible arrangements.

Put this together with the anti-angel provisions in the Dodd bill (which I think may have been slightly diluted recently), and it seems as if someone has declared a war on startups. Which is, in other words, a war on job creation and economic growth.

The Accumulation of Firms and the Predominance of New and Young Companies

This is a sequel to last week's post about moving from Paul's drunkard's walk to the accumulation of firms over time. Basically, the message of those two posts is that the internal dynamics of the American economy--lots of new companies founded each year, the exit of firms at all ages, the persistent predominance of young firms as the economy moves through time--make it highly probable that job creation will come from new and young companies rather than older, more established companies. (In these data that we're using, a firm is no longer classified as "young" once it reaches age 6, so the term "older," perhaps imprecisely, includes firms ages 6 and up.) Thus, when we say that new and young firms account for most net job creation in the U.S. economy, we are partly describing the reality of these firm dynamics.

This doesn't diminish the importance of these companies or the jobs they create. After all, the reality of these dynamics is premised on four things: a more or less steady inflow of startups; more or less consistent survival rates from year to year; comparable gross job creation and gross job destruction in older companies; and a higher number of jobs created at young firms (4 versus 1). These are not functions of what might be perceived as mathematical inevitability--they are the reasons behind the mathematical probabilities we are describing. If the level of firm formation were more volatile, if older companies created more jobs than they destroyed, if young firms were somehow suppressed in their hiring (through, perhaps, bailouts of larger, older companies; just speculating here)--if these variables changed, the dynamics of firm age through time, and subsequent job creation, would be different.

But, in recent history, these variables have all held and together they have created a picture that does, in fact, resemble something like mathematical inevitability, but which is probably more accurately described as a likelihood, or something of higher probability. In any given year over the past three decades, young firms (startups [age 0] and firms ages 1-5) have constituted the largest demographic of firms in the United States. Starting an economy at t=0, going out 25 years, the influx of new firms and the survival rates of firms over time generate this outcome. And, we might expect (provided the other variables are true) that the largest demographic sector will create the largest number of new jobs. This says nothing, of course, of innovation or productivity, subjects for another day.

Here, I want to supplement last week's post, which used average figures calculated from the Business Dynamics Statistics data, with the actual numbers from that dataset, which covers 1977-2005. That is, did reality conform to the stylized numbers we used last week? (The charts will not follow precisely the same format because last week's charts extrapolated out beyond 5 years on an annual basis, while the actual data aggregates firms into 5-year age categories after the fifth year: 6-10, 11-15, and so on.) We'll start, first, with the U.S. economy starting de novo in 1977, with only firms that came into existence that year. How, over the next 28 years, did the composition of firms by age change?

Here, startups (age 0, new firms founded each year) are broken out separately while all other firms are combined into 5-year categories. The data generally track the accumulation pattern revealed in last week's post: in any given year, young firms (ages 1-5) will quite naturally comprise the largest sector in terms of firm demographics. Note how few firms in 2005 are included in the 26-28 age category--these firms were founded in 1977-1979. By 2005, 19% of the firms founded in these three years remained. That may be more than expected, but using the survival line for firms founded for 1977 we can trace a slowly declining line of survival out two decades. If we imagine that the line continues on that downward slope for the next two decades, it appears as if very few firms in the economy survive more than four decades. Either those firms we all delight in describing as "dinosaurs" should properly be seen as remarkable achievements, or firm failure (over time) is a much more dominant force in the economy than we perhaps imagined. Probably both, and I'm probably simplifying here.

The advantage of using the real data from BDS is that we can include the "left censored" firms in our calculations, those companies founded prior to 1977 but for which we don't have age information. In 1977, then, these firms could be anywhere from age 1 to age 100. But we can track their survival after 1977 against all firms founded after that year. How long do these companies persist?

I included a brief explanation within the chart itself, but you can clearly see how these pre-1977 firms gradually decline in number over time, while new and young firms in any given year gradually get bigger in comparison. By 1988 (the circle), the pre-1977 firm group has shrunk such that it is now smaller each subsequent year compared to cohorts of new and young companies. By 2005, these firms still number 1.5 million, accounting for about one-fifth of all firms in the economy. This is a lot, but is an aggregate of every year before 1977, so there are probably a good number from the 1970s, a proportionately smaller number from the 1960s, and so on. 

Now, we can include these pre-1977 firms in our overall chart of firm demographics over time and compare firms of all ages:

This is actually an incredibly interesting chart, as the text insert fleshes out, but I'll repeat it here so you don't have to open the image itself. It shows two different ways in which firm composition changes and in which new and young firms consistently account for the bulk of firms in the economy. In 1977, the t=0 moment here, the economy is composed  of a class of startups (age 0) and all other firms existing that were founded before 1977. As the economy moves through time, you see four things happen. First, age 0 firms and age 1-5 firms account for a steady slice. Second, the overall number of firms accumulates. Third, the pre-1977 firms gradually decline in number. Fourth, post-1977 firms that age through time also diminish in terms of their numbers as fewer survive in subsequent years. So new and young firms dominate the economy (numerically) by two mechanisms: gradual disappearance of older firms and gradual disappearance of firms as they age. Same thing, different pathways (on this time scale).

Finally, we'll move to the percentage shares of each firm demographic (excluding pre-1977 firms here):

Once we get to a point where we have firms older than age 6 (and remember, the pre-1977 firms account for the missing shares here) in 1983, new and young companies account for between 30 and 40 percent of all firms in the economy. This percentage naturally falls over time, albeit slowly, as the overall number of firms grows, but this demographic of firms nonetheless comprises the largest demographic slice--a plurality, if you will--in each year, and this would persist over time.

So what, if anything, does this all mean? It means that new and young companies account for most new jobs in the economy in part because they are the largest demographic category of companies. It also means that job creation may actually be a secondary story here because this reality is a reflection of underlying dynamics that have been remarkably persistent over the past three decades. The United States has enjoyed a more or less steady level (and rate) of firm formation and survival rates for those firms have also been rather steady. Older companies, moreover, experience roughly equal levels of gross job creation and destruction, meaning their net job creation approaches zero.

It is entirely possible that these are transitory phenomena. As far as I can tell from the desultory data and research on firm formation prior to the 1970s, entrepreneurship (and subsequent survival rates) across the entire twentieth century have been remarkably consistent (I mention this, with an accompanying citation, in a forthcoming paper, so I'm not simply making this up). According to some Census data, for example, the number of new business created each year doubled from the 1940s to the 1990s--yet the country's population also doubled so the per capita rate of firm formation remained steady. Over the past thirty years, moreover, entrepreneurship rates have been remarkably steady, not declining as some have alleged. 

Yet we surely can't assume that the dynamics beneath such factors are immutable. The preponderance of research concerning firm demographics in many European countries, for example, holds that firm exit is a much smaller factor and that, consequently, unproductive firms simply continue to exist and new firms are dissuaded from entering. Large companies enjoy favorable policy and so the above charts might look quite different for other countries and clearly indicate that the dynamics can change. Even if part of what the above charts do is describe a mathematical reality, it could be considered progress if policymakers in Washington and elsewhere spoke in terms of this reality rather than giving undue attention to the largest companies in the economy (which, incidentally, often seek regulation as a means of protection from competition from startups). What this all means is that startups and young companies are no less important than we thought before--they are a robust and enduring dimension of the U.S. economy. It would be foolish, however, to assume that this is somehow a natural or permanent state of affairs--policy could easily be made to alter these dynamics for the worse.

From a Drunkard's Walk to a Pile of Drunks

This morning Paul wrote a very insightful post about job creation by new companies, trying to put things in a larger economic and mathematical context. (I am one of those (blessed? unfortunate?) people who thinks the game of baseball explains everything in life, including the economy, so it helps me to think of Paul's post in terms of the never-ending debate between sabermetricians and those who prefer a non-statistical view of baseball. In this view, Paul's post is the equivalent of putting a 5-hit game on Opening Day in a larger context of probability, rather than imbuing it with deeper meaning.)

I want to try to round out Paul's point by discussing the accumulating universe of firms over time (or, the accumulating pile of drunks in Paul's illustration). In an economy with a more or less steady influx of new firms and more or less consistent survival rates, we will have an accumulating number of firms as an economy moves through time. And, in any given year, "young" firms (5 years old and younger, including brand new startups) will constitute the largest percentage of the overall number of firms. By sheer arithmetic, then, shouldn't we expect that we will see a large number of new jobs from the largest cohort of firms? Maybe, maybe not.

Here is how it might work. Let's start with an economy with zero firms. In Year 1, we have 700,000 new businesses started (firms plus establishments; my thanks, by the way, to Mike Horrell for research assistance). Using survival rates calculated from the Business Dynamics Statistics database, we know that the average survival line for firms founded each year since 1977 looks like this:

So twenty percent of new firms survive to age one, two-thirds to age two, and so on to age 5. For age 6 and up, Mike used imputed survival lines extrapolated out from age 5. The real-world will be lumpier, but from what research I've seen from the SBA and others, the survival line post-age 5 is mostly a smooth downward slope. At some point, it likely becomes a near-asymptote, although some organizational research does suggest that survival for several decades, say to age 40 and beyond, is quite rare--conceivably, all firms die at some point.

Using these survival rates we can construct a chart showing the birth, death, and survival of firms as an economy moves forward from Year 1. In the first year, there are the 700,000 new firms. In Year 2, the initial batch of startups now consists of 552,440 firms, joined by the second year's round of incoming startups, another 700,000. So there are now 1,252,440 firms in this economy. If we continue this process out to, say, year 25, the process looks something like this:

 By year 10, firms ages 5 and younger account for nearly two-thirds of all firms. By the end of the series, in year 25, firms ages 5 and younger account for one-third of all firms. With assumed constancy of startups and survival rates, the absolute number of firms younger than age 5 remains the same but constitutes a decreasing proportion of the entire universe of firms. It remains true, however, that in any given year, young firms make up the largest cohort of companies. This would be reinforced if we added a constraint that no firm survives past, say, age 20. The point is that if the level of firm formation is steady (which it has been in the United States), and if survival rates for new firms have been consistent (ditto), than this is what an economy's population of firms would look like over 25 years.

What does this mean for job creation? It means we should expect the largest number of new jobs from the largest cohort of firms. I don't think is purely a function of the numbers, however--data from economists at the Census Bureau indicate that young firms add, on average, 3.7 (net) jobs per year. Firms ages 6 to 28, meanwhile, add (net) about one job per year. The oldest firms (age 29 plus) add nearly two and a half (net) jobs per year--still fewer than young firms. So it's true that young firms are adding one to two more (net) jobs per year than older firms, but this might be where Paul's drunkard's walk comes in.

So if young firms add 4 jobs per year, that means they add, in net terms, about eight million per year. In year 25, for the other 5 million firms in the economy, they will add about five million jobs; in year 10, they will add four million. (Note that in year 25 we haven't yet reached a point with any 29-year-old plus companies.) Many of those older firms will of course be larger than young companies, but we're talking about their net incremental contribution to American employment. 

None of this changes the fact that young firms account for most net job creation in the United States over time. What I'm wondering about is the why of this. Is it a subjective or normative comparison: young firms are "better" than all other companies? Or is it (partly) a function of mathematics and probability? What, if anything, does this mean for policy? It's never a bad thing when commentators and policymakers begin to realize the importance of new and young companies and stop seeing the economy solely in terms of our behemoth firms, but it's not clear what policies fall out of this if what we're talking about is a natural accumulation of firms and the ensuing natural distribution of net job creation. There is still plenty of dynamism to be worked in here--job creation, job destruction, the outstanding growth of certain companies--but this is (I think) an important point to make. 

It parallels something else I've been working on with regard to high-growth or top-performing firms. When we say that young firms create X% of jobs, or high-growth firms account for X% of job creation, should we be surprised that reality looks this way? Or, should we be more surprised if the economy did not look like this? In the case of high-growth firms, the question is: are we surprised that we find something resembling a Pareto distribution? Don't get me wrong--this does not belittle the importance of new and young firms and what they contribute in terms of jobs and innovations. Far from it. But it is important to keep things in perspective, mathematical and economic. Kind of like an Opening Day performance.

Startups in an Evolutionary Model

In describing how human knowledge advances, Donald Campbell devised the BVSR model to explain the evolutionary way in which knowledge accumulates. BVSR stands for Blind Variation and Selective Retention and is more or less natural selection applied to creativity and epistemology. Others have explored Campbell's with great insight and how it applies to fields such as organization science.

Evolutionary economics moves in and out of fashion but for the most part remains on the fringes of economic thought. Prompted in part by Paul's post earlier today, I'm wondering today about startup firms in a BVSR model of economic dynamics. It's no surprise (and, I don't think, controversial) that free market competition works through an evolutionary process of selection. Individuals and companies try various things (new products, services, processes) and their fate hinges on whether or not the market "selects" them vis-a-vis competing ideas. These new products and services are the variations in BVSR, whether radically new innovations or incremental improvements on something that already exists. We throw lots of spaghetti against the wall to see what sticks. Economic variation, of course, is not completely random since firms often seek to satisfy a previously identified market need or solve a heretofore unsolved problem. Variation is, however, blind in Campbell's sense, in that we do not know beforehand what will or will not succeed. "Blind" refers to our knowledge (more specifically, our lack of knowledge) about the consequences of any particular variation.

So we continuously introduce new variations into the market. The manner in which they are winnowed and propagated is "selective retention." Selection is clear: a new market variation either succeeds or it doesn't. Or, more precisely, it either survives (is selected) or doesn't survive (is not selected or selected against), with survival not always a proxy for subjective superiority. Here, it seems like the BVSR model advances somewhat beyond the standard view of the free-market-as-natural-selection (in addition to the explicit recognition that variations are blind). Once a variation is selected, what happens to it? It is retained, meaning it somehow propagates through the population. A variation doesn't merely survive--it grows and spreads. 

How would you increase economic growth or increase innovation through the BVSR model? Let's say each element is multiplied by the others, so growth or innovation is the result of V x S x R, all divided by B. Increasing any one element in the numerator should theoretically increase the product. (It's not clear that this should be true, by the way. I haven't convinced myself that multiplication is correct here. I suppose it's conceivable that it could or should be, for example, "+" R. This isn't a research paper and I'm just following an idea here, so please feel free to take issue with this. At this point, it's of de minimis concern.) According to this, then, you could increase growth or innovation by increasing variation (the introduction of new products and services), improving the selection process (so only "good" or "right" variations are selected), and improving retention, to the properly selected variations quickly achieve rapid scale and propagation, disseminating their benefits to everyone.

How would we approach startups here? Obviously, startups are one type of variation (at the population-level of the economy). They are selected for and against: roughly half of new firms (48%) survive to age five, with the survival curve slowly falling after that. (I've seen some data indicating that one-third of new firms survive to either age 7 or age 10.) Survival, of course, tells you little about success or quality, and selection in the case of firms is an ongoing process. Some research suggests that only the tiniest handful of companies survive for more than a few decades (suggesting that groups such as those companies on the Fortune 500 are both an incredibly small minority and, perhaps, a secondary story--maybe failure is the dominant story of economic selection). Retention could be either the organic growth of young companies or, I suppose, acquisition by larger, more established companies. (Revenue or employment growth or both would here serve as a proxy for another way of looking at retention: spread of a company's product through the market.) With the denominator, "Blind," we might want to reduce the blindness of our variations--that is, wouldn't we want to have a better idea of the prospective fate of new firms? Or, should B be another multiple here? Would increasing blindness be better because it would throw more of the burden onto the competitive process? Perhaps B is neutral here? That is, perhaps it cannot be increased or decreased? 

In any case, let's assume, with good reason, that startups are absolutely essential to innovation and economic growth. To increase these, what would we do with startups in the BVSR model? To begin with, could we reduce the blindness of a particular startup's fate, or the fate of all startups together? (It's not clear, moreover, what Blind should refer to here: mere survival to a certain age? Success, however nebulously defined?) Let's say Blind refers to the state of knowledge facing the founders of a new company: they do not know, and can't know, whether or not they will "succeed," however they define that term. (Although, if your objective is to simply work for yourself or the ability to wear flip-flops to work, then merely starting your own company can be considered success.) From a macro perspective, it's not clear that we can either reduce or increase blindness at the startup stage--the figure given above for survival to age five (48%) has been remarkably consistent across time. The survival rate for new firms, that is, doesn't appear to vary much founding year. There is some variance by sector but again, the survival lines within each sector are rather consistent, so it's not clear how we could either raise or lower the survival line. Of course, if survival rates have been consistent for thirty years, then perhaps the Blind element is neutralized: there is a 50-50 chance your firm will still be around five years from now.

Now, to Variation. Here, you would simply want to increase the number of new firms that are founded each year, with the expectation that trying more new variations would lead to more "good" things being selected and retained in the economy. An increase here means an increase there. I am sympathetic to this strategy, but I'm unclear as to how we do it. Firm formation in the United States has been pretty steady for two or three decades and the question of how we increase it is not so simple. Things like awareness and lowering barriers to entry are probably our best bets but these will vary by sector and geography and characteristics of the founder. All of this assumes, of course, that a basic increase in startups (more variation) will result in an increase in innovation and growth. And this assumes that we would see a similar proportion of innovative ideas and potentially successful firms in a larger pool of variations--is that a valid assumption? 

Selection of startups occurs through a variety of mechanisms. One, of course, is the market itself: you start a new firm and quickly find out whether or not it will selected in or out. If we increased the number of startups (increased V), then conceivably our selection mechanisms could remain the same, simply working on a larger population of firms. If, however, V remained constant, we might want to intensify S by looking more carefully (somehow) for promising ideas or "sure-thing" innovations. I suppose this is the role played by venture capital firms and accelerators such as Y Combinator. They have many entrepreneurs approach them and apply to them, but only select a few for funding or developing. Those that they do not select still go on to start new companies, so the claim of these particular selection mechanisms is that they are intensifying S so as to increase R: selecting the "best" of V, those with the most potential for retention and propagation by the market. As an overall strategy to enhance Selection, we would look to increase market competition in general, removing protective barriers around certain industries and firms, for example. A perennial complaint about some European economies (and conclusion of numerous McKinsey reports) is that they are not as competitive as the United States--stultified selection suppresses innovation and economic growth. It's also conceivable that simply increasing V would naturally increase S (they are, after all, multiplied by each other)--more firms overall would mean more firms competing. 

These notions of Selection, however, presume that any selection process, whether in biological evolution or in free market competition, is an optimizing one--that the "best" organism or population or idea or company always beats out inferior competitors. Adaptive fit, after all, implies such optimization. Yet we know that natural selection is only one way in which genes and organisms are winnowed and propagated. The role of accident and randomness in evolution cannot be forgotten: we like to think of dinosaurs as having met their proper evolutionary fate because they were all slow and dim-witted. But many evolutionary theorists have pointed out that, if a meteor or volcanic explosion did the dinosaurs in, then that isn't necessarily "natural selection" in terms of adaptation and competition. It was an exogenous event and the emerging population of smaller mammals happened to be better suited for survival. So, yes, an exogenous event "selected" out dinosaurs, but it wasn't necessarily the "optimizing" path we like to imagine. The same applies to the selection process in terms of firms and ideas: Silicon Valley bested Boston and Dallas because it had a better ecosystem, the selection process was more optimizing. But what if William Shockley's mother lived in Dallas, not Palo Alto? What if Frederick Terman had not contracted tuberculosis and had ended up returning to MIT? I realize these are entirely speculative and that the obvious riposte is, 'Well, that's just how things happened.' My point is simply that we shouldn't assume that Selection always implies optimizing; human behavior and group dynamics are such that the economic process contains plenty of satisficing behavior. (We also shouldn't forget that an entity such as a firm can become over-adapted to certain circumstances and thus too sessile to change; selection could work too well.)

Finally, how would we enhance Retention? What would this mean? It could entail somehow promoting those firms that are selected--say, those that survive to age six--via certain rewards such as a retroactive tax credit or something like that. Or, it could mean favoring those firms that grow rapidly in their first few years and have rapidly passed through V and S and we want to enhance their retention and propagation. It could mean reducing barriers to "scale," whether in the form of regulations, corporate taxes, whatever. (I continue to maintain, however, that the effect of certain taxes on entrepreneurship is not nearly as straightforward as some might like to believe.) Maybe we think of Retention as going public, in which case perhaps changes need to be made to Sarbanes-Oxley. Over the past few years, around 80% of VC exits have been acquisitions, not IPOs, and many of the companies coming out of accelerators are acquired by companies such as Google.

In any case, I don't know if this has added anything to the general discussion of entrepreneurship and economic growth or not. If we think about startups through the BVSR model, there are probably certain areas in which we can make changes to enhance the economic impact of startups, although some of them steer quite close to "picking winners." In general, as I said, I favor increasing V, but I'm as yet unclear as to how we go about doing this. Importantly, increased Variation should apply to firms of all types, not simply in favored sectors or those sectors we think (or would like to think) represent promising areas of innovation. Firm formation and innovation are compounding phenomena, so increasing the overall level of startups should (emphasize, should) raise our rates of innovation and growth, and this should be true whatever sector of the economy we are discussing. Information technology has been hugely important for American productivity, both in its production and its use in sectors like retail. We needed IT, but we also needed all those new retail outlets and supply chain innovations for the IT to become productive. It's possible that a BVSR-type of analysis in, say, 1995 might have concluded: we need more IT startups and fewer new retail stores. The economy might not have performed as well as it did.

More on Friedman

Here is another, albeit similar, take on one particular response to Thomas Friedman's Easter column celebrating startup companies. By the way, while you visit the PPI website, be sure to read Michael Mandel's policy memo on why the jobs crisis may well be an innovation crisis. 

Defending Thomas Friedman on Job Creation and Startups

In his column yesterday, New York Times columnist Thomas Friedman quoted Kauffman's Bob Litan about the importance of new and young firms to job creation and emphasized the importance of immigrants to firm formation. It was a trademark Friedman column: factoid, examples, quotations from experts, and concise policy lessons. I'm biased because Friedman used Kauffman data, but it was a good column.

Not everyone, however, wants to hear about the economic change that new firms and immigrants visit upon the U.S. economy. At Beat the Press, Dean Baker took issue with Friedman's column and Kauffman's data. With a layer of snark that is by now wearily standard in the blogosphere, Baker writes: "Friedman's conclusion about the special importance of new firms is utter nonsense." His logic:

The claim that most net new jobs came from new firms conceals the fact that existing firms added tens of millions of jobs in this 25-year period. Of course existing firms also lost tens of millions of jobs. We can say that the net job creation for existing firms was zero, but if we did not have an environment that was conducive for the job adders to grow (how many jobs did Microsoft, Apple, and Intel create after their first 5 years of existence?), then existing firms would have lost tens of millions more jobs.

Well, yes, that's true--and that's precisely the point. There are basically two ways to look at job creation in the economy: gross and net. On gross terms, large existing companies hire thousands of people each year, but they also see thousands of people leave, voluntarily or involuntarily. Gross job inflows and outflows in the American economy are enormous, an indicator of the ongoing and dynamic reallocation of resources that drives economic growth.

At the end of the day, however, if we want to keep pace with an expanding labor force (new entrants) and changing economy (the rise and fall of sectors and companies), what matters is net job creation. We have fifteen million people unemployed in the United States right now, and over the next several years net job creation has to proceed at a remarkable pace to not only provide jobs for this population but also create jobs for the millions of new people who will enter the labor force in the coming years. The last two years have seen the two biggest matriculating classes ever in American higher education, which means that in four or five years we will see a large influx of new graduates searching for jobs. How does Baker propose we keep pace with such growth?

From a macro perspective, for keeping pace with this growth, the only thing that matters is net job creation. It would be little consolation if we had 100 people looking for jobs, and large company ABC hired those 100 people but also fired 100 different people. For Baker, this is a good thing. And it is--for the 100 people who were hired. But what does Baker do with the 100 newly unemployed folks? Relate to them the wonders of big companies and their gross hiring?

Big, established companies are indisputably important--the symbiosis between new and old, small and large is a key strength of the U.S. economy. But we only get net job creation--a positive increment of new jobs to keep pace with labor force growth--from new and young companies. True, this population is highly dynamic, equally adept at creating jobs as eliminating them. Whereas this dynamic process works out to a net gain of zero in big companies, the net result among new and young companies is positive. If you subtract startups from the American economy over the past thirty years, there is only a handful of years in which the economy would have created a positive net number of new jobs. This makes sense as a brand new company can only create, not destroy jobs, but from the perspective of adding new jobs--for those 100 people above--this doesn't change the fact that new jobs come from new and young companies.

Baker also neglects to mention that once a company survives to a certain age (at age six a company is no longer classified in the data as "young") it becomes not an organic generator of jobs but an acquirer of new jobs via other companies, which are largely young and small. Baker asks, seemingly rhetorically, how many jobs Microsoft added over the age of five, but companies like Microsoft and Intel and eBay and others can generally only add a positive increment of net new jobs by acquiring young companies. So even the appearance of net job creation in our largest companies reflects the contribution of new and young firms. None of this, moreover, even begins to approach the role of new and young companies in innovation and economic expansion--not monolithic growth but the evolution of sectors and firms into new and unknown territory.

Baker also appears to cast cold water on Friedman's emphasis on the importance of immigrants, but doesn't dwell on it. There is, however, a faintly palpable nativist tinge in the comments to Baker's post. Why bring in "foreigners" to start companies? Don't we trust Americans? Nowhere, however, does Friedman (or Kauffman) claim that Americans are insufficient for entrepreneurship. In fact, immigrants who start companies in the United States create thousands of jobs for Americans--who could argue against that? For a country made great on a history of immigration, the United States risks falling prey to nativist sentiment from both the right and the left, which will inevitably stifle economic dynamism.

In criticizing Friedman (and Kauffman), Baker tries to cover his tracks with snark, wishing someone would revoke Friedman's license to discuss economics. In an altogether brilliant post last week, Michael Pettis observed, "Snarkiness is always a sign of intellectual insecurity or confusion, and never an indication of insight." Rather than snark, Baker should consider how his vision of a big-companies-only economy would lead to stultified job growth, harming the people he claims to want to protect.